notameStats

notameStats provides univariate and multivariate statistics for feature prioritization in untargeted LC-MS metabolomics research.

Key Features:

• Univariate statistics: Provides statistical methods for single-feature analysis in metabolomics data.
• Multivariate statistics: Provides statistical methods for analyzing multiple features simultaneously in metabolomics data.
• Feature prioritization: Enables ranking and selection of metabolomic features for downstream analysis.

Scientific Applications:

• Untargeted LC-MS metabolomics: Supports statistical analysis of liquid chromatography-mass spectrometry-based metabolic profiling data.

Methodology:

The sources do not provide detailed methodological description beyond univariate and multivariate statistical approaches for feature prioritization.